SoroushVahidi/scidocs huggingface dataset:
The Dual-State Theory of Prefrontal Cortex Dopamine Function with Relevance to Catechol-<ce:italic>O</ce:italic>-Methyltransferase Genotypes and Schizophrenia
(2008)

There is now general consensus that at least some of the cognitive deficits in schizophrenia are related to dysfunctions in the prefrontal cortex (PFC) dopamine (DA) system. At the cellular and synaptic level, the effects of DA in PFC via D1- and D2-class receptors are highly complex, often apparently opposing, and hence difficult to understand with regard to their functional implications. Biophysically realistic computational models have provided valuable insights into how the effects of DA on PFC neurons and synaptic currents as measured in vitro link up to the neural network and cognitive levels. They suggest the existence of two discrete dynamical regimes, a D1-dominated state characterized by a high energy barrier among different network patterns that favors robust online maintenance of information and a D2-dominated state characterized by a low energy barrier that is beneficial for flexible and fast switching among representational states. These predictions are consistent with a variety of electrophysiological, neuroimaging, and behavioral results in humans and nonhuman species. Moreover, these biophysically based models predict that imbalanced D1:D2 receptor activation causing extremely low or extremely high energy barriers among activity states could lead to the emergence of cognitive, positive, and negative symptoms observed in schizophrenia. Thus, combined experimental and computational approaches hold the promise of allowing a detailed mechanistic understanding of how DA alters information processing in normal and pathological conditions, thereby potentially providing new routes for the development of pharmacological treatments for schizophrenia.
KEEPING YOUR HEADCOUNT WHEN ALL ABOUT YOU ARE LOSING THEIRS : DOWNSIZING , VOLUNTARY TURNOVER RATES , AND THE MODERATING ROLE OF HR PRACTICES
(2009)

Although both downsizing and voluntary turnover have been topics of great interest in the organizational literature, little research has addressed the possible relationship between the two. Using organization-level data from multiple industries, we first investigate whether downsizing predicts voluntary turnover rates. Second, to lend support to our causal model, we examine whether this relationship is mediated by aggregated levels of organizational commitment. Third, we test whether the downsizing-turnover rate relationship: (1) is mitigated by HR practices that tend to embed employees in the organization or convey procedural fairness; and (2) is strengthened by HR practices that enhance career development. Results support the hypothesized main, mediated, and moderated effects.
Bias in Wikipedia
(2017)

While studies have shown that Wikipedia articles exhibit quality that is comparable to conventional encyclopedias, research still proves that Wikipedia, overall, is prone to many different types of Neutral Point of View (NPOV) violations that are explicitly or implicitly caused by bias from its editors. Related work focuses on political, cultural and gender bias. We are developing an approach for detecting both explicit and implicit bias in Wikipedia articles and observing its evolution over time. Our approach is based on different factors of bias, with the most important ones being language style, editors, and citations. In this paper we present the approach, methodology and a first analysis.
Touching the void: direct-touch interaction for intangible displays
(2010)

In this paper, we explore the challenges in applying and investigate methodologies to improve direct-touch interaction on intangible displays. Direct-touch interaction simplifies object manipulation, because it combines the input and display into a single integrated interface. While traditional tangible display-based direct-touch technology is commonplace, similar direct-touch interaction within an intangible display paradigm presents many challenges. Given the lack of tactile feedback, direct-touch interaction on an intangible display may show poor performance even on the simplest of target acquisition tasks. In order to study this problem, we have created a prototype of an intangible display. In the initial study, we collected user discrepancy data corresponding to the interpretation of 3D location of targets shown on our intangible display. The result showed that participants performed poorly in determining the z-coordinate of the targets and were imprecise in their execution of screen touches within the system. Thirty percent of positioning operations showed errors larger than 30mm from the actual surface. This finding triggered our interest to design a second study, in which we quantified task time in the presence of visual and audio feedback. The pseudo-shadow visual feedback was shown to be helpful both in improving user performance and satisfaction.
Urban computing with taxicabs
(2011)

Urban computing for city planning is one of the most significant applications in Ubiquitous computing. In this paper we detect flawed urban planning using the GPS trajectories of taxicabs traveling in urban areas. The detected results consist of 1) pairs of regions with salient traffic problems and 2) the linking structure as well as correlation among them. These results can evaluate the effectiveness of the carried out planning, such as a newly built road and subway lines in a city, and remind city planners of a problem that has not been recognized when they conceive future plans. We conduct our method using the trajectories generated by 30,000 taxis from March to May in 2009 and 2010 in Beijing, and evaluate our results with the real urban planning of Beijing.
Network diversity and economic development.
(2010)

Social networks form the backbone of social and economic life. Until recently, however, data have not been available to study the social impact of a national network structure. To that end, we combined the most complete record of a national communication network with national census data on the socioeconomic well-being of communities. These data make possible a population-level investigation of the relation between the structure of social networks and access to socioeconomic opportunity. We find that the diversity of individuals' relationships is strongly correlated with the economic development of communities.
Tracking "gross community happiness" from tweets
(2012)

Policy makers are calling for new socio-economic measures that reflect subjective well-being, to complement traditional measures of material welfare as the Gross Domestic Product (GDP). Self-reporting has been found to be reasonably accurate in measuring one's well-being and conveniently tallies with sentiment expressed on social media (e.g., those satisfied with life use more positive than negative words in their Facebook status updates). Social media content can thus be used to track well-being of individuals. A question left unexplored is whether such content can be used to track well-being of entire physical communities as well. To this end, we consider Twitter users based in a variety of London census communities, and study the relationship between sentiment expressed in tweets and community socio-economic well-being. We find that the two are highly correlated: the higher the normalized sentiment score of a community's tweets, the higher the community's socio-economic well-being. This suggests that monitoring tweets is an effective way of tracking community well-being too.
Modeling Dominance in Group Conversations Using Nonverbal Activity Cues
(2009)

Dominance - a behavioral expression of power - is a fundamental mechanism of social interaction, expressed and perceived in conversations through spoken words and audiovisual nonverbal cues. The automatic modeling of dominance patterns from sensor data represents a relevant problem in social computing. In this paper, we present a systematic study on dominance modeling in group meetings from fully automatic nonverbal activity cues, in a multi-camera, multi-microphone setting. We investigate efficient audio and visual activity cues for the characterization of dominant behavior, analyzing single and joint modalities. Unsupervised and supervised approaches for dominance modeling are also investigated. Activity cues and models are objectively evaluated on a set of dominance-related classification tasks, derived from an analysis of the variability of human judgment of perceived dominance in group discussions. Our investigation highlights the power of relatively simple yet efficient approaches and the challenges of audiovisual integration. This constitutes the most detailed study on automatic dominance modeling in meetings to date.
Rule-Based Neural Networks for Classification and Probability Estimation
(1992)

In this paper we propose a network architecture that combines a rule-based approach with that of the neural network paradigm. Our primary motivation for this is to ensure that the knowledge embodied in the network is explicitly encoded in the form of understandable rules. This enables the network's decision to be understood, and provides an audit trail of how that decision was arrived at. We utilize an information theoretic approach to learning a model of the domain knowledge from examples. This model takes the form of a set of probabilistic conjunctive rules between discrete input evidence variables and output class variables. These rules are then mapped onto the weights and nodes of a feedforward neural network resulting in a directly specified architecture. The network acts as parallel Bayesian classifier, but more importantly, can also output posterior probability estimates of the class variables. Empirical tests on a number of data sets show that the rule-based classifier performs comparably with standard neural network classifiers, while possessing unique advantages in terms of knowledge representation and probability estimation.
Wind Speed and Rotor Position Sensorless Control for Direct-Drive PMG Wind Turbines
(2010)

This paper proposes a wind speed and rotor position sensorless control for wind turbines directly driving permanent magnetic generators (PMGs). A sliding-mode observer is designed to estimate the rotor position of the PMG by using the measured stator currents and the commanded stator voltages obtained from the control scheme of the machine-side converter of the PMG wind turbine. The rotor speed of the PMG (i.e., the turbine shaft speed) is estimated from its back electromotive force using a model adaptive reference system observer. Based on the measured output electrical power and estimated rotor speed of the PMG, the mechanical power of the turbine is estimated by taking into account the power losses of the wind turbine generator system. A back-propagation artificial neural network is then designed to estimate the wind speed in real time by using the estimated turbine shaft speed and mechanical power. The estimated wind speed is used to determine the optimal shaft speed reference for the PMG control system. Finally, a sensorless control is developed for the PMG wind turbines to continuously generate the maximum electrical power without using any wind speed or rotor position sensors. The validity of the proposed estimation and control algorithms are shown by simulation studies on a 3-kW PMG wind turbine and are further demonstrated by experimental results on a 300-W practical PMG wind turbine.
Cloud-Based Big Data Management and Analytics for Scholarly Resources: Current Trends, Challenges and Scope for Future Research
(2016)

With the shifting focus of organizations and governments towards digitization of academic and technical documents, there has been an increasing need to use this reserve of scholarly documents for developing applications that can facilitate and aid in better management of research. In addition to this, the evolving nature of research problems has made them essentially interdisciplinary. As a result, there is a growing need for scholarly applications like collaborator discovery, expert finding and research recommendation systems. This research paper reviews the current trends and identifies the challenges existing in the architecture, services and applications of big scholarly data platform with a specific focus on directions for future research.
An effect analysis of industry 4.0 to higher education
(2016)

From history to the present day, especially in the field of technology is provided a wide range of developments. The most important of these developments has achieved the realization of the industrial revolution, has led to play a leading role in the production is done by human beings. The effects on production of industry 4.0 emerging with this mind is very important. The qualified employees should be trained to make the necessary preparations for the company in this period, it is experiencing the fourth industrial revolution. Therefore, the impacts on higher education of industry 4.0 are examined in this paper. The importance in education of industry 4.0 has revealed with statistical data presented in this study.
Locating the fovea center position in digital fundus images using thresholding and feature extraction techniques
(2013)

A new methodology for detecting the fovea center position in digital retinal images is presented in this paper. A pixel is firstly searched for within the foveal region according to its known anatomical position relative to the optic disc and vascular tree. Then, this pixel is used to extract a fovea-containing subimage on which thresholding and feature extraction techniques are applied so as to find fovea center. The methodology was evaluated on 1200 fundus images from the publicly available MESSIDOR database, 660 of which present signs of diabetic retinopathy. In 93.92% of these images, the distance between the methodology-provided and actual fovea center position remained below 1/4 of one standard optic disc radius (i.e., 17, 26, and 27 pixels for MESSIDOR retinas of 910, 1380 and 1455 pixels in size, respectively). These results outperform all the reviewed methodologies available in literature. Its effectiveness and robustness with different illness conditions makes this proposal suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection.
Modular ATRON: modules for a self-reconfigurable robot
(2004)

This paper describes the mechanical and electrical design of a new lattice based self-reconfigurable robot, called the ATRON. The ATRON system consists of several fully self-contained robot modules, each having their own processing power, power supply, sensors and actuators. The ATRON modules are roughly spheres with equatorial rotation. Each module can be connected to up to eight neighbors through four male and four female connectors. In this paper, we describe the realization of the design, both the mechanics and the electronics. Details on power sharing and power consumption is given. Finally, this paper includes a brief outline of our future work on the ATRON system.
Consumer Intention to Shop Online : B 2 C E-Commerce in Developing Countries
(2013)

The development of dot com companies in 90s opened a new door of sales and revenue generation for the businesses world wide. The number of online shoppers increased dramatically within a very short span of time. While some people found it a convenient and sophisticated way of shopping, others remained reluctant to adopt this medium. Different factors are considered responsible for this variation in online behavior. Most of the researches on this topic are conducted in the developed countries so there is a need to study the phenomenon from the developing countries perspective. Based on existing literature on the topic a research model was developed which was further tested by means of a survey.
Coordinated Charging of Plug-In Hybrid Electric Vehicles to Minimize Distribution System Losses
(2011)

As the number of plug-in hybrid vehicles (PHEVs) increases, so might the impacts on the power system performance, such as overloading, reduced efficiency, power quality, and voltage regulation particularly at the distribution level. Coordinated charging of PHEVs is a possible solution to these problems. In this work, the relationship between feeder losses, load factor, and load variance is explored in the context of coordinated PHEV charging. From these relationships, three optimal charging algorithms are developed which minimize the impacts of PHEV charging on the connected distribution system. The application of the algorithms to two test systems verifies these relationships approximately hold independent of system topology. They also show the additional benefits of reduced computation time and problem convexity when using load factor or load variance as the objective function rather than system losses. This is important for real-time dispatching of PHEVs.
Analysis of PWM nonlinearity in non-inverting buck-boost power converters
(2008)

This paper focuses on the non-inverting buck- boost converter operated as either buck or boost converter. It is shown that a pulse-width modulation (PWM) discontinuity around buck/boost mode transition can result in substantial increases in output voltage ripple. The effect of the PWM nonlinearity is studied using periodic steady state analysis to quantify the worst case ripple voltage in terms of design parameters. Furthermore, a bifurcation analysis shows that the PWM discontinuity leads to quasi- periodic route to chaos, which results in erratic operation around the buck/boost mode transition. The increased ripple is a very significant problem when the converter is used as a power supply for an RF power amplifier, as is the case in WCDMA handsets. An approach is proposed to remove the discontinuity which results in reduced output voltage ripple, at the expense of reduced efficiency, as demonstrated on an experimental prototype.
A cortical–hippocampal system for declarative memory
(2000)

Recent neurobiological studies have begun to reveal the cognitive and neural coding mechanisms that underlie declarative memory — our ability to recollect everyday events and factual knowledge. These studies indicate that the critical circuitry involves bidirectional connections between the neocortex, the parahippocampal region and the hippocampus. Each of these areas makes a unique contribution to memory processing. Widespread high-order neocortical areas provide dedicated processors for perceptual, motor or cognitive information that is influenced by other components of the system. The parahippocampal region mediates convergence of this information and extends the persistence of neocortical memory representations. The hippocampus encodes the sequences of places and events that compose episodic memories, and links them together through their common elements. Here I describe how these mechanisms work together to create and re-create fully networked representations of previous experiences and knowledge about the world.
Plans and resource-bounded practical reasoning
(1988)

An architecture for a rational agent must allow for means end reason ing for the weighing of competing alternatives and for interactions between these two forms of reasoning Such an architecture must also address the problem of resource boundedness We sketch a solution of the rst problem that points the way to a solution of the second In particular we present a high level speci cation of the practical reasoning component of an archi tecture for a resource bounded rational agent In this architecture a major role of the agent s plans is to constrain the amount of further practical reasoning she must perform Bratman Israel and Pollack
A survey of autonomic communications
(2006)

Autonomic communications seek to improve the ability of network and services to cope with unpredicted change, including changes in topology, load, task, the physical and logical characteristics of the networks that can be accessed, and so forth. Broad-ranging autonomic solutions require designers to account for a range of end-to-end issues affecting programming models, network and contextual modeling and reasoning, decentralised algorithms, trust acquisition and maintenance---issues whose solutions may draw on approaches and results from a surprisingly broad range of disciplines. We survey the current state of autonomic communications research and identify significant emerging trends and techniques.
Design of Hybrid Excited Synchronous Machine for Electrical Vehicles
(2015)

This paper deals with the optimal design of a new synchronous motor particularly suitable for electric vehicles. The unique advantage of this motor is its possibility to realize field weakening at high speeds, which is the most important demand for such drives. The main design goal is to identify the dimensions of certain crucial regions of the machine in order to avoid saturation of the iron and to minimize the mass to volume ratio, while simultaneously maximizing the torque. The originality of the contribution is manifold: formulating the design problem in multiobjective terms, solving it by means of evolutionary computing, solving the associated direct problem based on a three-dimensional finite element analysis (3-D-FEA) field model, considering a reduced set of design variables by means of response surface method, referring to a real-life problem.
Criteria-Based Requirements Prioritization for Software Product Management
(2008)

Meeting stakeholders requirements and expectations becomes one of the critical aspects on which any software organization in market-driven environment focus on, and pays a lot of efforts and expenses to maximize the satisfaction of their stakeholders. Therefore identifying the software product release contents becomes one of the critical decisions for software product success. Requirements prioritization refers to that activity through which product releases contents that maximize stakeholder satisfaction can be identified. This makes it one of the most important component of software requirement decision support in incremental software development [8]. This paper illustrates the Criteria-Based requirement prioritization approach for software product management. The technique proposed on this paper designed based on the Hierarchical Cumulative Voting (HCV) and Value-Oriented Prioritization (VOP) techniques. The proposed technique, Value-Oriented HCV (VOHCV) can select the best candidate requirements for each release based on the stakeholders input values for each requirement. These values reflect the importance of each requirement in terms of associated anticipated cost, technical risk, relative impact, market-related aspects and perceived value to the stakeholder. The VOHCV inherits the strengths of the HCV and VOP techniques. It also provides a mechanism that takes different stakeholders’ aspects into account while selecting the best candidate release requirement, to maximize stakeholders’ value and satisfaction [11].